As gas turbine engines operate, the engines may become less efficient due to a combination of factors including wear and damage. Because the rate at which engines deteriorate depends on several operational factors, the rate is difficult to predict, and as such, engine components are typically scheduled for maintenance based on a pre-selected number of hours or cycles. The pre-selected number is typically conservatively selected based on a number of factors including past component experience and past engine performance estimates. If a component fails, a predetermined diagnosis routine is followed to identify and replace the failed component.
To estimate engine performance and to find engine sensor faults, selected engine parameters are sensed and monitored to estimate an overall loss in the engine performance. Typically, rotor speeds, exhaust gas temperatures, and fuel flows are corrected or normalized for variations in operating conditions, and these normalized parameters are trended, i.e., their changes over short and long periods of time are plotted, and used to forecast when engine refurbishment is required. Additionally, immediate engine repairs may be scheduled if comparing current trending values to prior trending values illustrates abrupt changes, or step changes.
While currently the overall engine performance and quality is inferred by assessing engine sensor values during operation and long-term trending, the quality level of individual gas turbine components, such as fan, compressor or turbines, is not estimated and continuously updated during operation.
What is needed is the ability to forecast the remaining engine life before an engine overhaul is required, through the estimation and tracking of engine component quality. What is also needed is the ability to define the scope of the required engine overhaul, and to detect and isolate engine component damage and faults.